Understanding the determinants of infant and under-five mortality rates: a multivariate decomposition analysis of Demographic and Health Surveys in Ghana, 2003, 2008 and 2014

Effect of maternal migration on under-five mortality in the Navrongo HDSS area

INTRODUCTION

Mortality under five years is an important indicator and a significant index for assessing the health and general wellbeing of a country. Even though global efforts to reduce under-five mortality have yielded some positive results, the rates are still high in most low- and middle-income countries. There is general consensus that migration and its associated remittances alleviate poverty at the rural places of origin. This tends to improve household living standards and leads to improvement in child health and survival. This paper seeks to investigate the impact of maternal migration on under-five mortality in two districts in the Upper East Region of Ghana.

METHODS

This study used data from the Health and Demographic Surveillance System (HDSS) of the Navrongo Health Research Centre (NHRC) in Ghana. All children (20,990) born in the study area between 2000 and 2014 were included in the analysis. The outcome variable in the analysis was the survival status of the children (dead or alive). The main independent variable is migration status of the mothers (migrants and non-migrants). The Proportional Hazard Model, with a Weibull distribution, was used to examine the effect of the independent variables on the survival outcomes of the children.

RESULTS

The results showed that children of migrant (in-migrant or return migrant) mothers are 49% less likely to die compared with children of non-migrant mothers [aOR = 0.513; (CI = 0.451-0585)]. In terms of migration duration before return, survival benefit was highest for children whose mothers had been away for one year and more. Other factors that were associated with increased risk of under-five mortality include children of mothers without education, children of mothers age 15-19 years, children born outside health facility, first order births, multiple births and children without grandmothers in their households.

CONCLUSION

The study has established that maternal migration, irrespective duration, contribute to child survival. Specifically, children of migrant mothers have a better survival chance than children of non-migrant mothers. To improve child survival in these poor rural settings, we recommend the promotion of conducive migration opportunities to enable women to earn some income to support their households in terms of childcare and survival.

Modeling time to death for under-five children in Malawi using 2015/16 Demographic and Health Survey: a survival analysis

BACKGROUND

Malawi has one of the highest under-five mortality rates in Sub Sahara Africa. Understanding the factors that contribute to child mortality in Malawi is crucial for the development and implementation of effective interventions to reduce child mortality. The aim of this study is to use survival analysis in modeling time to death for under-five children in Malawi. In turn, identify potential risk factors for child mortality and inform the development of interventions to reduce child mortality in the country.

METHOD

This study used data from all births that occurred in the five years leading up to the 2015/16 Malawi Demographic and Health Survey. The Frailty hazard model was applied to predict infant survival in Malawi. In this analysis, the outcome of interest was death and it had two possible outcomes: "dead" or "alive". Age at death was regarded as the survival time variable. Infants who were still alive at the time of the study as of the day of the interview were considered as censored observations in the analysis.

RESULTS

A total of 17,286 live births born during the 5 years preceding the survey were analysed. The study found that the risk of death was higher among children born to mothers aged 30-39 and 40 or older compared to teen mothers. Infants whose mothers attended fewer than four antenatal care visits were also found to be at a higher risk of death. On the other hand, the study found that using mosquito nets and early breastfeeding were associated with a lower risk of death, as were being male and coming from a wealthier household.

CONCLUSION

The study reveals a notable decline in infant mortality rates as under-five children age, underscoring the challenge of ensuring newborn survival. Factors such as maternal age, birth order, socioeconomic status, mosquito net usage, early breastfeeding initiation, geographic location, and child's sex are key predictors of under-five mortality. To address this, public health strategies should prioritize interventions targeting these predictors to reduce under-five mortality rates.

Infant mortality in Ghana: investing in health care infrastructure and systems

Child and infant mortality is a global problem. Almost half of deaths of children under age 5 years occur in the neonatal period, the first 28 days of life, with 2.4 million neonatal deaths globally in 2020. Sub-Saharan Africa has disproportionately high numbers of neonatal deaths. Ghana's neonatal mortality rate is 22.8 per 1000 live births and remains behind targets set by the United Nations Sustainable Development Goals. Quality antenatal care, postnatal monitoring, breastfeeding support, and postnatal family planning are important in preventing neonatal deaths. While Ghana has made progress in making care more financially accessible, it has not been matched with the improvements in the critical infrastructure required to ensure quality health care. The improvements have also not eliminated out-of-pocket costs for care, which have hindered progress in decreasing infant mortality. Policymakers should consider investments in health care infrastructure, including expanding public-private partnerships. Policies that improve workforce development programs, transportation infrastructure, and health insurance systems improvements are needed.

Determinants of under-five mortality in Sri Lanka: A multilevel analysis of 2016 Sri Lankan DHS data

Under-five mortality (U5M) is considered a major public health issue directly impacts a country's development. This study analyzed the prognostic factors of U5M in Sri Lanka using data from the 2016 Demographic and Health Survey (DHS) of 8123 children. The study employed both a binary logistic regression model (BLRM) and a binary logistic random intercept multilevel model (BLRIMM) and compared the accuracy of each model's prediction percentage. The results showed that the BLRIMM had a higher correct prediction percentage (98.67%) compared to the BLRM (98.31%). The study found that children who were not breastfed (Odds Ratio (OR) = 116.74, 95% Confidence Interval (CI) = 62.97-216.41), were part of multiple births (OR = 3.73, 95% CI = 1.21-11.51), did not have a normal delivery (OR = 1.86, 95% CI = 1.11-3.12), were born to mothers who had experienced previous miscarriages or child loss (OR = 2.27, 95% CI = 1.26-4.11), and were born to mothers with a higher Body Mass Index (BMI) (OR = 1.05, 95% CI = 1.003-1.10) had higher odds of U5M. The odds of U5M were found to be lower among Buddhists (OR = 0.06, 95% CI = 0.01-0.50), Hindus (OR = 0.05, 95% CI = 0.01-0.46), and Roman Catholics (OR = 0.032, 95% CI = 0.003-0.307) compared to the "Other Religions" category in the dataset. The estimated covariance parameter of the random intercept (0.8231, p-value = 0.0405) indicated significant unobserved cluster-level variation in U5M. The study's results emphasize the importance of addressing religion related differences of U5M and improving maternal education regarding healthy lifestyle, proper food intake, the significance of breastfeeding, safe delivery methods, safety measures during pregnancy and childbirth in cases of multiple births, and proper child care after birth.

Maternal health care policy intervention and its impact on perinatal mortality outcomes in Ghana: evidence from a quasi-experimental design

OBJECTIVE

This study aimed to evaluate the impact of Ghana's free maternal health care policy on stillbirth and perinatal death since its implementation a decade ago.

STUDY DESIGN

The study used the propensity score matching method, a quasi-experimental design technique and secondary data to construct two groups of mothers with a history of perinatal deaths who subscribed to the 'free' maternal health care policy versus mothers who did not.

METHOD

The study merged two rounds of repeated cross-sectional data sets obtained from the Ghana Demographic and Health Survey (GDHS), 2008 and 2014, and generated exposure variables; pregnant women policy holding status and outcome variables; stillbirth and perinatal death by constructing binary outcomes from the under-five mortality variables of the DHS data sets. Fetal and early neonatal deaths within the data set were categorized into two groups: those exposed to the free maternal health care policy and those who did not. The propensity scores of the two groups were then generated and analyzed after checking for bias and common support. The analysis applied sample weighting to account for clustering and stratification due to the complex design of the DHS. All analyses were done with STATA 15 and adjusted for confounding using independent covariates.

RESULTS

Stillbirth (43.3%) and perinatal death (60.2%) were high in the intervention group compared to the comparison group, and the differences were statistically significant (stillbirth, 0.0156, and perinatal death, 0.0012). Stillbirth and perinatal deaths were 12 and 13 percentage points higher in the intervention group, and these were statistically significant: adj. coef. = 0.12; 95% CI: [0.03-0.19]; P = 0.005 and adj. coef. = 0.13; 95% CI: [0.03-0.22]; P = 0.005.

CONCLUSION

The results show that stillbirth and perinatal death were high in the maternal health care policy group, poorly reflecting as outcomes. However, the percentage point difference between stillbirth and perinatal death suggests a decline in early neonatal mortality and a positive impact of the 'free' maternal health care policy on perinatal death over stillbirth.

Prevalence and risk factors associated with under-five mortality in the Solomon Islands: an investigation from the 2015 Solomon Islands demographic and health survey data

Background

Annually, over five million children die before their fifth birthday worldwide, with 98% of these deaths occurring in low-and middle-income countries. The prevalence and risks for under-five mortality are not well-established for the Solomon Islands.

Methods

We used the Solomon Islands Demographic and Health Survey 2015 data (SIDHS 2015) to estimate the prevalence and risk factors associated with under-five mortality.

Findings

Neonatal, infant, child and under-five mortality prevalence were 8/1000, 17/1000, 12/1000 and 21/1000 live births, respectively. After adjustment for potential confounders, neonatal mortality was associated with no breastfeeding [aRR 34.80 (13.60, 89.03)], no postnatal check [aRR 11.36 (1.22, 106.16)], and Roman Catholic [aRR 3.99 (1.34, 11.88)] and Anglican [aRR 2.78 (0.89, 8.65); infant mortality to no breastfeeding [aRR 11.85 (6.15, 22.83)], Micronesian [aRR 5.54 (1.67, 18.35)], and higher birth order [aRR 2.00 (1.03, 3.88)]; child mortality to multiple gestation [aRR 6.15 (2.08, 18.18)], Polynesian [aRR 5.80 (2.48, 13.53)], and Micronesian [aRR 3.65 (1.46, 9.10)], cigarette and tobacco [aRR 1.77 (0.79, 3.96)] and marijuana use [aRR 1.94 (0.43, 8.73)] and rural residence [aRR 1.85 (0.88, 3.92)]; under-five mortality to no breastfeeding [aRR 8.65 (4.97, 15.05)], Polynesian [aRR 3.23 (1.09, 9.54)], Micronesian [aRR 5.60 (2.52, 12.46)], and multiple gestation [aRR 3.34 (1.26, 8.88)]. Proportions of 9% for neonatal and 8% of under-five mortality were attributable to no maternal tetanus vaccination.

Interpretation

Under-five mortality in the Solomon Islands from the SIDHS 2015 data was attributable to maternal health, behavioural, and sociodemographic risk factors. We recommended future studies to confirm these associations.

Funding

No funding was declared to support this study directly.

Machine Learning Algorithms for understanding the determinants of under-five Mortality

BACKGROUND

Under-five mortality is a matter of serious concern for child health as well as the social development of any country. The paper aimed to find the accuracy of machine learning models in predicting under-five mortality and identify the most significant factors associated with under-five mortality.

METHOD

The data was taken from the National Family Health Survey (NFHS-IV) of Uttar Pradesh. First, we used multivariate logistic regression due to its capability for predicting the important factors, then we used machine learning techniques such as decision tree, random forest, Naïve Bayes, K- nearest neighbor (KNN), logistic regression, support vector machine (SVM), neural network, and ridge classifier. Each model's accuracy was checked by a confusion matrix, accuracy, precision, recall, F1 score, Cohen's Kappa, and area under the receiver operating characteristics curve (AUROC). Information gain rank was used to find the important factors for under-five mortality. Data analysis was performed using, STATA-16.0, Python 3.3, and IBM SPSS Statistics for Windows, Version 27.0 software.

RESULT

By applying the machine learning models, results showed that the neural network model was the best predictive model for under-five mortality when compared with other predictive models, with model accuracy of (95.29% to 95.96%), recall (71.51% to 81.03%), precision (36.64% to 51.83%), F1 score (50.46% to 62.68%), Cohen's Kappa value (0.48 to 0.60), AUROC range (93.51% to 96.22%) and precision-recall curve range (99.52% to 99.73%). The neural network was the most efficient model, but logistic regression also shows well for predicting under-five mortality with accuracy (94% to 95%)., AUROC range (93.4% to 94.8%), and precision-recall curve (99.5% to 99.6%). The number of living children, survival time, wealth index, child size at birth, birth in the last five years, the total number of children ever born, mother's education level, and birth order were identified as important factors influencing under-five mortality.

CONCLUSION

The neural network model was a better predictive model compared to other machine learning models in predicting under-five mortality, but logistic regression analysis also shows good results. These models may be helpful for the analysis of high-dimensional data for health research.

Carbon dioxide emission and health outcomes: is there really a nexus for the Nigerian case?

Health outcomes in sub-Saharan Africa are characteristically poor and Nigeria is no exception. Despite the recorded decline in infant and under five mortality rates in Nigeria, they still remain relatively high showing a poor status of the population's health. Carbon dioxide emission continues to fluctuate at high levels probably due to the increasing use of non renewable energy forms for economic activities mostly requiring energy consumption. This study examines the health consequences of environmental quality due to carbon dioxide emission in Nigeria for the period 1980 to 2016. Using two health outcome measures and decomposing carbon dioxide emission by sector and type of fuel consumed, a bound cointegration approach and an autoregressive distributed lag model were also employed. The results and a sensitivity analysis revealed that aggregate carbon dioxide emission significantly explained both infant mortality and under five mortality rates. However, when disaggregated, carbon dioxide emission from solid fuel had the greatest contribution to poor health outcomes.

Assessing Individual- and Community-Level Variability in Predictors of Neonatal, Infant, and Under-Five Child Mortality in Ethiopia Using a Multilevel Modeling Approach

Background: In low-and middle-income countries, child mortality rates are basic indicators of a country’s socio-economic situation and quality of life. The Ethiopian government is currently working to reduce child mortality to accomplish its long-term development goals. Using data from the Ethiopian Mini Demographic and Health Survey, 2019, this study analyzed the determinants of child mortality in Ethiopia. Methods: A total of 4806 children were considered in the final analyses. Multivariate analysis was used to estimate the effects of the predictors simultaneously on each child mortality outcome. Results: The findings revealed that 31.6% of children died during the neonatal stage, 39.1% during the infant stage, and 48.5% during the under-five stage. Variation in child mortality was discovered between Ethiopian community clusters, with the result of heterogeneity between clusters on newborn mortality (χ2 = 202.4, p-value < 0.0001), (χ2 = 777.35, p-value < 0.0001), and (χ2 = 112.92, p-value < 0.0001). Children’s neonatal, infant, and under-five mortality intracluster correlation coefficient (ICC) were 0.35, 0.33, and 0.36, respectively, across communities. Conclusions: In Ethiopia, under-five mortality remains a serious public health issue, with wide variations and high rates among community clusters. Intervention measures focusing on lowering rates of household poverty, increasing education opportunities, and improving access to health care could assist in reducing child mortality in Ethiopia.

Socio-economic and proximate determinants of under-five mortality in Guinea

BACKGROUND

The death of children under-five years is one of the critical issues in public health and improving child survival continues to be a matter of urgent concern. In this paper, we assessed the proximate and socio-economics determinants of child mortality in Guinea.

METHODS

Using the 2018 Guinea Demographic and Health Survey (GDHS), we extracted demographic and mortality data of 4,400 children under-five years. Both descriptive and multivariable logistic regression analyses were conducted.

RESULTS

Under-five mortality was 111 deaths per 1,000 live births in Guinea. The likelihood of death was higher among children born to mothers who belong to other religions compared to Christians (aOR = 2.86, 95% CI: 1.10-7.41), smaller than average children compared to larger than average children (aOR = 1.97, 95% CI: 1.28-3.04) and those whose mothers had no postnatal check-up visits after delivery (aOR = 1.72, 95% CI: 1.13-2.63). Conversely, the odds of death in children with 2-3 birth rank & >2 years of birth interval compared to ≥4 birth rank and ≤2 years of birth interval were low (aOR = 0.53, 95% CI: 0.34-0.83).

CONCLUSION

We found that household/individual-level socioeconomic and proximate factors predict under-five mortality in Guinea. With just about a decade left to the 2030 deadline of the Sustainable Development Goals (SDGs), concerted efforts across all key stakeholders, including government and development partners, need to be geared towards implementing interventions that target these predictors.

Determinant factors of under-five mortality in Southern Nations, Nationalities and People's region (SNNPR), Ethiopia

Background

Child mortality is a key indicator of the performance of the health system of a nation. Impressive progress in the reduction of under-five mortality has been made in Ethiopia. However, still there are some regions where the under-five mortality rates are high. Southern Nations, Nationalities, and Peoples’ Region (SNNPR) is among those regions in Ethiopia with high under-five mortality rates. This study aimed to identify the determinant factors of under-five mortality in SNNPR.

Methods

Data used for the study were drawn from the 2016 EDHS. A total of 1277 under-five children were included in the study. A multivariable logistic regression model was fitted to identify determinant factors associated with under-five mortality.

Results

Children with second or third birth order (OR = 1.316, 95% CI: (1.097, 2.343)), fourth or fifth birth order (OR = 1.934, 95% CI: (1.678, 3.822)), sixth or above birth order (OR = 3.980, 95% CI: (2.352, 6.734)) were significantly associated with increased risk of under-five mortality as compared to those with first birth order. Increased risk of under-five mortality was also significantly associated with a family size of five or more (OR = 3.397, 95% CI: (1.702, 6.782)) as compared to the family size of less than five; smaller size at birth (OR = 1.714, 95% CI: (1.120, 2.623)) as compared to larger size at birth; multiple births (OR = 1.472, 95% CI: (1.289, 2.746)) as compared to singletons. On the other hand, female children (OR = 0.552, 95% CI: (0.327, 0.932)), children born at health institutions (OR = 0.449, 95% CI: (0.228, 0.681)) and children who were breastfed (OR = 0.657, 95% CI: (0.393, 0.864)) were significantly associated with decreased risk of under-five mortality as compared to male children, those born at home and those who were not breastfed respectively.

Conclusions

Sex of a child, birth order, size of a child at birth, place of delivery, birth type, breastfeeding status, and family size were significant factors associated with under-five mortality in SNNPR, Ethiopia. Thus, planning and implementing relevant strategies that focus on those identified determinant factors of under-five mortality is required for the improvement of child survival in SNNPR, Ethiopia.

Are maternal and child health initiatives helping to reduce under-five mortality in Ghana? Results of a quasi-experimental study using coarsened exact matching

BACKGROUND

Despite a 53 % decline in under-five mortality (U5M) worldwide during the period of the Millennium Development Goals (MDGs), U5M remains a challenge. Under-five mortality decline in Ghana is slow and not parallel with the level of coverage of child health interventions. The interventions promoted to improve child survival include early initiation of breastfeeding, clean postnatal care, and skilled delivery. This study sought to assess the effectiveness of these interventions on U5M in Ghana.

METHODS

A quasi-experimental study was conducted using secondary data of the 2008 and 2014 Ghana Demographic and Health Surveys. Coarsened Exact Matching and logistic regression were done. The interventions assessed were iron intake, early initiation of breastfeeding, clean postnatal care, hygienic disposal of stool, antenatal care visits, skilled delivery, intermittent preventive treatment of malaria in pregnancy, and tetanus toxoid vaccine.

RESULTS

There were 2,045 children under-five years and 40 (1.9 %) deaths in 2008. In 2014, the total number of children under-five years was 4,053, while deaths were 53(1.2 %). In 2014, children less than one month old formed 1.6 % of all children under-five years, but 47.8 % of those who died. Mothers who attended four or more antenatal care visits were 78.2 % in 2008 and 87.0 % in 2014. Coverage levels of improved sanitation and water connection in the home were among the lowest, with 11.6 % for improved sanitation and 7.3 % for water connection in the home in 2014. Fifty-eight (58), 1.4 %, of children received all the eight (8) interventions in 2014, and none of those who received all these interventions died. After controlling for potential confounders, clean postnatal care was associated with a 66% reduction in the average odds of death (aOR = 0.34, 95 %CI:0.14-0.82), while early initiation of breastfeeding was associated with a 62 % reduction in the average odds of death (aOR = 0.38, 95 % CI: 0.21-0.69).

CONCLUSIONS

Two (clean postnatal care and early initiation of breastfeeding) out of eight interventions were associated with a reduction in the average odds of death. Thus, a further decline in under-five mortality in Ghana will require an increase in the coverage levels of these two high-impact interventions.

Factors influencing under-five mortality in rural- urban Ghana: An applied survival analysis

OBJECTIVES

This paper uses a survival analysis technique to examine socio-economic and demographic factors that influence under-five mortality for rural and urban Ghana.

METHOD

The paper employs the Breslow Method for Ties for survival probability and uses data for the 2014 Ghana Demographic and Health Survey (GDHS). Data on some 5884 children was also generated through the interview of 4086 women aged 15-49. They indicated the birth histories of the children under five years.

RESULTS

The study finds the most significant socio-economic determinants of a child survival in Ghana to be maternal age, mother's education, household wealth index quintile, place of delivery and birth order. The influence of these determinants on child survival differ from urban to rural.

CONCLUSION

The survival probabilities of these explanatory variables are different in the rural area from the urban area. Therefore, it is imperative to scale up efforts in the rural area to ensure children live up to age five.

Revisit the correlates of infant mortality in Bangladesh: findings from two nationwide cross-sectional studies

OBJECTIVE

The main objective of this study is to investigate how the direction and strength of the association between infant mortality and its predictors are changing over time in Bangladesh using a nationally representative sample for the period 2011-2014.

DESIGN, SETTING AND PARTICIPANTS

Data from two repeatedly cross-sectional Bangladesh Demographic and Health Surveys (BDHSs) for the years 2011 and 2014 were used. A total of 7664 (with 312 infant death) and 7048 (with 264 infant death) complete cases, respectively, from BDHS 2011 and 2014 datasets were included in the study.

METHODS

Cox's proportional hazard model with robust standard error (SE) that adjusts for the complex survey design characteristics was implemented to assess how the risk factors associated with infant mortality change their paths.

RESULTS

Results reflected that administrative division remained as a potential risk factor of infant death for both periods. Household's socioeconomic status, father's employment status, age difference between parents turned out to be potential risk factors in 2014, though they did not show any significant association with infant death in the year 2011. In contrast to 2011, mothers' individual-level characteristics such as age at childbirth, education, media exposure, employment status did not remain as significant risk factors for infant death in 2014. Younger fathers increased the burden of death among infants of adolescent mothers. At higher order births, the burden of infant death significantly shifted from rural to urban areas. From the year 2011 to 2014, urban areas achieved socioeconomic equity in infant survival, while the extent of inequity was increased in rural areas.

CONCLUSION

Community-based programmes should be designed for urban mothers who are expecting higher order births. To eradicate the socioeconomic inequity in infant survival, the government should design strong and sustainable maternal and child healthcare facilities, especially for rural areas.

The impact of child health interventions and risk factors on child survival in Kenya, 1993-2014: a Bayesian spatio-temporal analysis with counterfactual scenarios

BACKGROUND

During the millennium development goals period, reduction in under-five mortality (U5M) and increases in child health intervention coverage were characterised by sub-national disparities and inequities across Kenya. The contribution of changing risk factors and intervention coverage on the sub-national changes in U5M remains poorly defined.

METHODS

Sub-national county-level data on U5M and 43 factors known to be associated with U5M spanning 1993 and 2014 were assembled. Using a Bayesian ecological mixed-effects regression model, the relationships between U5M and significant intervention and infection risk ecological factors were quantified across 47 sub-national counties. The coefficients generated were used within a counterfactual framework to estimate U5M and under-five deaths averted (U5-DA) for every county and year (1993-2014) associated with changes in the coverage of interventions and disease infection prevalence relative to 1993.

RESULTS

Nationally, the stagnation and increase in U5M in the 1990s were associated with rising human immunodeficiency virus (HIV) prevalence and reduced maternal autonomy while improvements after 2006 were associated with a decline in the prevalence of HIV and malaria, increase in access to better sanitation, fever treatment-seeking rates and maternal autonomy. Reduced stunting and increased coverage of early breastfeeding and institutional deliveries were associated with a smaller number of U5-DA compared to other factors while a reduction in high parity and fully immunised children were associated with under-five lives lost. Most of the U5-DA occurred after 2006 and varied spatially across counties. The highest number of U5-DA was recorded in western and coastal Kenya while northern Kenya recorded a lower number of U5-DA than western. Central Kenya had the lowest U5-DA. The deaths averted across the different regions were associated with a unique set of factors.

CONCLUSION

Contributions of interventions and risk factors to changing U5M vary sub-nationally. This has important implications for targeting future interventions within decentralised health systems such as those operated in Kenya. Targeting specific factors where U5M has been high and intervention coverage poor would lead to the highest likelihood of sub-national attainment of sustainable development goal (SDG) 3.2 on U5M in Kenya.

Sex differences and factors associated with disability among Ghana's workforce: a nationally stratified cross-sectional study

OBJECTIVE

This study was conducted to estimate the prevalence of disability and associated factors and further quantify the associated sex differential among Ghana's workforce aged 15+ years.

DESIGN

A nationally stratified cross-sectional study.

SETTING

Ghana.

PARTICIPANTS

Individuals aged 15 years and above.

OUTCOME MEASURE

Disability that limits full participation in life activities.

METHODS

Three predictive models involving Poisson, logistic and probit regression were performed to assess the association between disability and covariates. Modified Poisson multivariate decomposition analysis method was employed to assess sex differential and associated factors using Stata V.16.

RESULTS

The prevalence of disability was 2.1% (95% CI 1.2 to 2.4), and the risk of disability among males was approximately twice compared with females (Poisson estimate: adjusted prevalence ratio (95% CI)=1.94 (1.46 to 2.57); logistic estimate: aOR (95% CI)=2.32 (1.73 to 3.12)). Male sex increased the log odds of disability by 0.37 (probit estimate, aβ (95% CI)=0.37 (0.23 to 0.50)). The variability in age group, marital status, household (HH) size, region, place of residence, relationship to HH head, hours of work per week and asset-based wealth were significantly associated with disability-based sex differential. (Significant increased endowment: β×10^-3 (95% CI×10^-3)=-37.48 (-56.81 to -18.16) and significant decreased coefficient: β×10^-3 (95% CI×10^-3)=42.31 (21.11 to 63.49).) All disability participants were challenged with activities of daily living, limiting them in full participation in life activities such as mobility, work and social life.

CONCLUSION

The magnitude of experiencing disability among working males was nearly twice that of females. Sex differentials were significantly associated with age groups, marital status, HH size, region of residence, relationship to HH head, hours of work per week and wealth. Our findings amass the provisional needs of persons living with a disability that are indicators to consider to achieve the United Nations Convention on the Rights of Persons with Disabilities Article 10. In addition, formulation of workplace policies should adopt a gender-sensitive approach to reduce disparities and eliminate disability in the target population.

Identifying Factors Associated with Neonatal Mortality in Sub-Saharan Africa using Machine Learning

This study aimed at identifying the factors associated with neonatal mortality. We analyzed the Demographic and Health Survey (DHS) datasets from 10 Sub-Saharan countries. For each survey, we trained machine learning models to identify women who had experienced a neonatal death within the 5 years prior to the survey being administered. We then inspected the models by visualizing the features that were important for each model, and how, on average, changing the values of the features affected the risk of neonatal mortality. We confirmed the known positive correlation between birth frequency and neonatal mortality and identified an unexpected negative correlation between household size and neonatal mortality. We further established that mothers living in smaller households have a higher risk of neonatal mortality compared to mothers living in larger households; and that factors such as the age and gender of the head of the household may influence the association between household size and neonatal mortality.

Intimate partner violence, contextual factors and under-5 mortality: a multilevel analysis of cross-sectional surveys from 20 Sub-Saharan African countries

BACKGROUND

Under-5 mortality remains a public health concern in low-income and middle-income countries. Africa contributes about one-fifth of the burden of global under-5 mortality; intimate partner violence (IPV) and polygyny, which are highly prevalent on the continent, have been linked to under-5 mortality at the individual level. This study examined the relationship between IPV and polygyny as contextual factors and the experience of under-5 mortality among women in Sub-Saharan Africa (SSA).

METHODS

We used data from the Demographic and Health Surveys (DHS) of 20 African countries with available data between 2010 and 2018 as of April 2020. We defined the experience of under-5 mortality as a woman's loss of at least one child before their fifth birthday. The DHS primary sampling unit was used to define contextual factors. The study involved a multilevel logistic regression analysis of 227 121 women of childbearing age (15-49).

RESULTS

A quarter (24.5%) of women have lost at least one child under 5 years old, more than two-thirds (40.1%) have experienced at least one form of IPV, and about two-thirds of women were in polygynous union. Our multilevel logistic regression showed that parity, polygynous union and experience of IPV were strongly associated with women's experience of under-5 mortality. The results showed that 39.9% and 19.2% of variances in odds of a woman losing a child before their fifth birthday are attributable to community-level and country-level factors, respectively. Contextual prevalence of IPV, polygynous union and gender equity attenuate the strength of associations observed at the individual level. The interaction between contextual prevalence of polygyny and IPV exacerbates the risk of under-5 mortality. Women in SSA countries with higher Human Development Index were less likely to experience under-5 mortality.

CONCLUSION

This study established that beyond individual-level effects, contextual prevalence of IPV and polygyny and their interactions shape women's experience of under-5 mortality in Africa. In designing policies and interventions to address under-5 mortality, contextual factors, especially those linked to culturally laden social norms and practices, must be considered to ensure effectiveness and sustainable impact.

Under-Five Mortality and Associated Risk Factors in Rural Settings of Ethiopia: Evidences from 2016 Ethiopian Demographic and Health Survey

Background. Evidence shows that in Ethiopia, a gradual decrease of under-five mortality is observed, but it is still high in the rural settings of the country. We are motivated to investigate the socioeconomic, demographic, maternal and paternal, and child-related associated risk factors of under-five mortality given birth from rural resident mothers. Methods. Demographic and Health Survey data from Ethiopia (2016) were used for analysis. The chi-square test of association and logistic regression were used to determine the associated risk factors of under-five children mortality. Study Settings. Rural Ethiopia. Results. Secondary school and above completed fathers (AOR = 0.77; 95% CI: 0.63–0.94) and primary school completed mothers (AOR = 0.82; 95% CI: 0.72–0.93); multiple twin child (AOR = 4.50; 95% CI: 3.38–5.98); public sector delivery (AOR = 0.65; 95% CI: 0.55–0.76); had working of mother (AOR = 1.28; 95% CI: 1.16–1.42) and of father (AOR = 1.45; 95% CI: 1.25–1.69); mothers aged above 16 at first birth (AOR = 0.41; 95% CI: 0.37–0.45); breastfeeding (AOR = 0.60; 95% CI: 0.55–0.66); birth order of 2-3 (AOR = 1.18; 95% CI: 1.02–1.37); religious belief of Muslim (AOR = 1.20; 95% CI: 1.02–1.41); users of contraceptive method (AOR = 0.80; 95% CI: 0.71–0.90); vaccinated child (AOR = 0.52; 95% CI: 0.46–0.60); family size of 4–6 (AOR = 0.74; 95% CI: 0.63–0.86) and of seven and above (AOR = 0.44; 95% CI: 0.36–0.52); mother’s age group: aged 20–29 (AOR = 3.88; 95% CI: 3.08–4.90), aged 30–39 (AOR = 16.29; 95% CI: 12.66–20.96), and aged 40 and above (AOR = 55.97; 95% CI: 42.27–74.13); number of antenatal visits: 1–3 visits (AOR = 0.50; 95% CI: 0.43–0.58), and four and above visits (AOR = 0.46; 95% CI: 0.39–0.54); and preceding birth interval of 25–36 months (AOR = 0.55; 95% CI: 0.48–0.62) and above 36 months (AOR = 0.30; 95% CI: 0.26–0.34) are significant determinant factors of under-five mortality in rural settings. Conclusions. Differences in regions, educated parents, born in singleton, public sector delivery, nonavailability of occupation of parents, mothers older than 16 at first birth, breastfeeding, use of a contraceptive method, child vaccination, higher number of family size, repeated antenatal visits, and preceding birth interval play a significant role regarding the survival of under-five children. These, among other differences, should be addressed decisively as part of any upcoming strategic interventions to improve the survival of children in line with the target of 2030 Sustainable Development Goals (SDGs).

Proximate Determinants of Under-Five Mortality in Ethiopia: Using 2016 Nationwide Survey Data

INTRODUCTION

Although there has been a remarkable decline in under-five mortality through the decades, it is still highest in socio-economically disadvantaged countries, including Ethiopia. The benefits of reducing under-five mortality have been highly emphasized in the ambitious target of Sustainable Development Goals. The risk factors of under-five mortality have not been exhaustively researched in Ethiopia using recent nationwide survey data.

OBJECTIVE

This study aimed to determine the risk factors of under-five mortality using the recent nationwide survey data.

METHOD

The data source for this study was the 2016 Ethiopian Demographic and Health Survey. Bivariate and multivariable logistic regression analysis was conducted and statistical significance was declared at p value < 0.05.

RESULTS

The data for a total of 10,641 under-five children were analyzed and the under-five mortality rate was 67 per 1000 live births in this study. In the final model, rural residence (AOR=2.0, [1.20, 3.30], P=0.008), mothers who gave birth with preceding birth intervals of shorter than 24 months (AOR=2.12, CI=[1.72, 2.61], P<0.000), multiple births (AOR=4.74, CI=[3.34, 6.69], P<0.000), very small size of child at birth (AOR=1.43, CI= [1.10, 1.85], P=0.007), and being male (AOR=1.30, CI=[1.07, 1.57], P<0.008) showed significant association with under-five mortality compared to their counterparts.

CONCLUSION

Under-five mortality was significantly associated with place of residence, preceding birth interval, plurality, size of child at birth, and sex of the child. Thus, special emphasis should be placed on children with rural residence, preceding birth interval of shorter than 24 months, very small size of the child at birth, and male children.